Exp 2 (Pilot)
Simon Stephan
# data file needs to be in the same directory as the R-Markdown-Script
library(readr)
tdata <- read_delim("tdata_final.txt",
delim = "\t", escape_double = FALSE,
trim_ws = TRUE)## Rows: 122 Columns: 12
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (7): subj_code, desktop_conf, attent_conf, Cond_sum, explanation, gender...
## dbl (5): condition, instr_tests, Rating_CC, Rating_SE, age
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.1 Results
1.1 Demographics
# demographics
min(tdata$age)## [1] 19max(tdata$age)## [1] 76mean(tdata$age)## [1] 38.7377sd(tdata$age)## [1] 12.82676# 1 = male, 2 = female, 3 = other
table(tdata$gender)##
## 1: male 2: female
## 46 761 = male, 2 = female, 3 = non-binary
2 Graphs
## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.## Warning: `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.
3 binary and continuous seperate
binary <- subset(tdata_long, Cond_sum == "binary_raidal" | Cond_sum == "binary_channel")
binary$Cond_sum <- factor(binary$Cond_sum, levels = c("binary_channel","binary_raidal"), labels = c("binary & channel", "binary & radial"))
continuous <- subset(tdata_long, Cond_sum != "binary_raidal" & Cond_sum != "binary_channel")
continuous$Cond_sum <- factor(continuous$Cond_sum,
levels = c("cont_channel_limited", "cont_channel_ulimited", "cont_radial_limited", "cont_radial_unlimited"),
labels = c("channel & limited", "channel & unlimited", "radial & limited", "radial & unlimited"))## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.## Warning: `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.
## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.## Warning: `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.
## `fun.y` is deprecated. Use `fun` instead.
4 append additional factors
continuous$transmission[continuous$Cond_sum == "channel & unlimited" | continuous$Cond_sum == "channel & limited"] <- "channel"## Warning: Unknown or uninitialised column: `transmission`.continuous$transmission[continuous$Cond_sum == "radial & unlimited" | continuous$Cond_sum == "radial & limited"] <- "radial"
continuous$energy[continuous$Cond_sum == "channel & unlimited" | continuous$Cond_sum == "radial & unlimited"] <- "unlimited"## Warning: Unknown or uninitialised column: `energy`.continuous$energy[continuous$Cond_sum == "channel & limited" | continuous$Cond_sum == "radial & limited"] <- "specific"binary$transmission[binary$Cond_sum == "binary & channel"] <- "channel"## Warning: Unknown or uninitialised column: `transmission`.binary$transmission[binary$Cond_sum == "binary & radial"] <- "radial"5 Descriptive Stats
## : Rating_SE
## : channel
## : specific
## median mean SE.mean CI.mean.0.95 var std.dev
## 1.00000000 0.93000000 0.02523573 0.05281899 0.01273684 0.11285762
## coef.var
## 0.12135228
## ------------------------------------------------------------
## : Rating_CC
## : channel
## : specific
## median mean SE.mean CI.mean.0.95 var std.dev
## 0.2500000 0.2750000 0.0250000 0.0523256 0.0125000 0.1118034
## coef.var
## 0.4065578
## ------------------------------------------------------------
## : Rating_SE
## : radial
## : specific
## median mean SE.mean CI.mean.0.95 var std.dev
## 0.80000000 0.70952381 0.06283189 0.13106502 0.08290476 0.28793187
## coef.var
## 0.40581002
## ------------------------------------------------------------
## : Rating_CC
## : radial
## : specific
## median mean SE.mean CI.mean.0.95 var std.dev
## 0.40000000 0.44285714 0.04759523 0.09928191 0.04757143 0.21810875
## coef.var
## 0.49250364
## ------------------------------------------------------------
## : Rating_SE
## : channel
## : unlimited
## median mean SE.mean CI.mean.0.95 var std.dev
## 1.00000000 0.82000000 0.05600752 0.11722508 0.06273684 0.25047324
## coef.var
## 0.30545517
## ------------------------------------------------------------
## : Rating_CC
## : channel
## : unlimited
## median mean SE.mean CI.mean.0.95 var std.dev
## 0.65000000 0.62500000 0.05843350 0.12230272 0.06828947 0.26132255
## coef.var
## 0.41811608
## ------------------------------------------------------------
## : Rating_SE
## : radial
## : unlimited
## median mean SE.mean CI.mean.0.95 var std.dev
## 0.80000000 0.72500000 0.05019698 0.10506349 0.05039474 0.22448772
## coef.var
## 0.30963824
## ------------------------------------------------------------
## : Rating_CC
## : radial
## : unlimited
## median mean SE.mean CI.mean.0.95 var std.dev
## 0.70000000 0.66500000 0.05393710 0.11289164 0.05818421 0.24121403
## coef.var
## 0.36272787by(binary$value, list(binary$variable, binary$transmission), stat.desc , basic = FALSE)## : Rating_SE
## : channel
## median mean SE.mean CI.mean.0.95 var std.dev
## 1.00000000 0.79523810 0.05454408 0.11377696 0.06247619 0.24995238
## coef.var
## 0.31431137
## ------------------------------------------------------------
## : Rating_CC
## : channel
## median mean SE.mean CI.mean.0.95 var std.dev
## 0.80000000 0.75238095 0.05372729 0.11207316 0.06061905 0.24620936
## coef.var
## 0.32724029
## ------------------------------------------------------------
## : Rating_SE
## : radial
## median mean SE.mean CI.mean.0.95 var std.dev
## 0.90000000 0.75000000 0.06386664 0.13367441 0.08157895 0.28562029
## coef.var
## 0.38082705
## ------------------------------------------------------------
## : Rating_CC
## : radial
## median mean SE.mean CI.mean.0.95 var std.dev
## 0.90000000 0.81500000 0.05040624 0.10550148 0.05081579 0.22542358
## coef.var
## 0.276593356 Statistical Test
library(afex)## ************
## Welcome to afex. For support visit: http://afex.singmann.science/## - Functions for ANOVAs: aov_car(), aov_ez(), and aov_4()
## - Methods for calculating p-values with mixed(): 'S', 'KR', 'LRT', and 'PB'
## - 'afex_aov' and 'mixed' objects can be passed to emmeans() for follow-up tests
## - NEWS: emmeans() for ANOVA models now uses model = 'multivariate' as default.
## - Get and set global package options with: afex_options()
## - Set orthogonal sum-to-zero contrasts globally: set_sum_contrasts()
## - For example analyses see: browseVignettes("afex")
## ************##
## Attache Paket: 'afex'## Das folgende Objekt ist maskiert 'package:lme4':
##
## lmerlibrary(emmeans)
a1 <- aov_car(value ~ variable*transmission*energy + Error(subj_code/(variable)), continuous)## Converting to factor: transmission, energy## Contrasts set to contr.sum for the following variables: transmission, energya1## Anova Table (Type 3 tests)
##
## Response: value
## Effect df MSE F ges p.value
## 1 transmission 1, 77 0.05 0.60 .004 .442
## 2 energy 1, 77 0.05 11.77 *** .070 <.001
## 3 transmission:energy 1, 77 0.05 0.00 <.001 .986
## 4 variable 1, 77 0.05 69.76 *** .314 <.001
## 5 transmission:variable 1, 77 0.05 13.80 *** .083 <.001
## 6 energy:variable 1, 77 0.05 22.39 *** .128 <.001
## 7 transmission:energy:variable 1, 77 0.05 3.23 + .021 .076
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1# same ANOVA as before
lmeModel <- lmer(value ~ variable*transmission*energy + (1|subj_code), data=continuous)## boundary (singular) fit: see help('isSingular')# follow-up analysis
ls1 <- lsmeans(a1, c("variable","transmission","energy")) # joint evaluation (basically gives the same table)
ls1## variable transmission energy lsmean SE df lower.CL upper.CL
## Rating_SE channel specific 0.930 0.0513 77 0.828 1.032
## Rating_CC channel specific 0.275 0.0483 77 0.179 0.371
## Rating_SE radial specific 0.710 0.0500 77 0.610 0.809
## Rating_CC radial specific 0.443 0.0471 77 0.349 0.537
## Rating_SE channel unlimited 0.820 0.0513 77 0.718 0.922
## Rating_CC channel unlimited 0.625 0.0483 77 0.529 0.721
## Rating_SE radial unlimited 0.725 0.0513 77 0.623 0.827
## Rating_CC radial unlimited 0.665 0.0483 77 0.569 0.761
##
## Confidence level used: 0.95ls2 <- lsmeans(a1, c("variable","transmission")) # joint evaluation (basically gives the same table)
ls2## variable transmission lsmean SE df lower.CL upper.CL
## Rating_SE channel 0.875 0.0363 77 0.803 0.947
## Rating_CC channel 0.450 0.0341 77 0.382 0.518
## Rating_SE radial 0.717 0.0358 77 0.646 0.789
## Rating_CC radial 0.554 0.0337 77 0.487 0.621
##
## Results are averaged over the levels of: energy
## Confidence level used: 0.95ls3 <- lsmeans(a1, c("variable","energy")) # joint evaluation (basically gives the same table)
ls3## variable energy lsmean SE df lower.CL upper.CL
## Rating_SE specific 0.820 0.0358 77 0.748 0.891
## Rating_CC specific 0.359 0.0337 77 0.292 0.426
## Rating_SE unlimited 0.772 0.0363 77 0.700 0.845
## Rating_CC unlimited 0.645 0.0341 77 0.577 0.713
##
## Results are averaged over the levels of: transmission
## Confidence level used: 0.95# same ANOVA as before
lmeModel <- lmer(value ~ variable*Cond_sum + (1|subj_code), data=tdata_long)
# follow-up analysis
ls1 <- lsmeans(lmeModel, c("Cond_sum","variable")) # joint evaluation (basically gives the same table)
ls1## Cond_sum variable lsmean SE df lower.CL upper.CL
## binary_channel Rating_SE 0.795 0.0509 223 0.695 0.896
## binary_raidal Rating_SE 0.750 0.0521 223 0.647 0.853
## cont_channel_limited Rating_SE 0.930 0.0521 223 0.827 1.033
## cont_channel_ulimited Rating_SE 0.820 0.0521 223 0.717 0.923
## cont_radial_limited Rating_SE 0.710 0.0509 223 0.609 0.810
## cont_radial_unlimited Rating_SE 0.725 0.0521 223 0.622 0.828
## binary_channel Rating_CC 0.752 0.0509 223 0.652 0.853
## binary_raidal Rating_CC 0.815 0.0521 223 0.712 0.918
## cont_channel_limited Rating_CC 0.275 0.0521 223 0.172 0.378
## cont_channel_ulimited Rating_CC 0.625 0.0521 223 0.522 0.728
## cont_radial_limited Rating_CC 0.443 0.0509 223 0.343 0.543
## cont_radial_unlimited Rating_CC 0.665 0.0521 223 0.562 0.768
##
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95ls2 <- lsmeans(a1, c("variable","transmission")) # joint evaluation (basically gives the same table)
ls2## variable transmission lsmean SE df lower.CL upper.CL
## Rating_SE channel 0.875 0.0363 77 0.803 0.947
## Rating_CC channel 0.450 0.0341 77 0.382 0.518
## Rating_SE radial 0.717 0.0358 77 0.646 0.789
## Rating_CC radial 0.554 0.0337 77 0.487 0.621
##
## Results are averaged over the levels of: energy
## Confidence level used: 0.95ls3 <- lsmeans(a1, c("variable","energy")) # joint evaluation (basically gives the same table)
ls3## variable energy lsmean SE df lower.CL upper.CL
## Rating_SE specific 0.820 0.0358 77 0.748 0.891
## Rating_CC specific 0.359 0.0337 77 0.292 0.426
## Rating_SE unlimited 0.772 0.0363 77 0.700 0.845
## Rating_CC unlimited 0.645 0.0341 77 0.577 0.713
##
## Results are averaged over the levels of: transmission
## Confidence level used: 0.95###############
# a conditional analysis
# simple main effects
t <- pairs(ls1) # compares rep-measure differences separately for each between-factor level
t## contrast estimate
## binary_channel Rating_SE - binary_raidal Rating_SE 0.04524
## binary_channel Rating_SE - cont_channel_limited Rating_SE -0.13476
## binary_channel Rating_SE - cont_channel_ulimited Rating_SE -0.02476
## binary_channel Rating_SE - cont_radial_limited Rating_SE 0.08571
## binary_channel Rating_SE - cont_radial_unlimited Rating_SE 0.07024
## binary_channel Rating_SE - binary_channel Rating_CC 0.04286
## binary_channel Rating_SE - binary_raidal Rating_CC -0.01976
## binary_channel Rating_SE - cont_channel_limited Rating_CC 0.52024
## binary_channel Rating_SE - cont_channel_ulimited Rating_CC 0.17024
## binary_channel Rating_SE - cont_radial_limited Rating_CC 0.35238
## binary_channel Rating_SE - cont_radial_unlimited Rating_CC 0.13024
## binary_raidal Rating_SE - cont_channel_limited Rating_SE -0.18000
## binary_raidal Rating_SE - cont_channel_ulimited Rating_SE -0.07000
## binary_raidal Rating_SE - cont_radial_limited Rating_SE 0.04048
## binary_raidal Rating_SE - cont_radial_unlimited Rating_SE 0.02500
## binary_raidal Rating_SE - binary_channel Rating_CC -0.00238
## binary_raidal Rating_SE - binary_raidal Rating_CC -0.06500
## binary_raidal Rating_SE - cont_channel_limited Rating_CC 0.47500
## binary_raidal Rating_SE - cont_channel_ulimited Rating_CC 0.12500
## binary_raidal Rating_SE - cont_radial_limited Rating_CC 0.30714
## binary_raidal Rating_SE - cont_radial_unlimited Rating_CC 0.08500
## cont_channel_limited Rating_SE - cont_channel_ulimited Rating_SE 0.11000
## cont_channel_limited Rating_SE - cont_radial_limited Rating_SE 0.22048
## cont_channel_limited Rating_SE - cont_radial_unlimited Rating_SE 0.20500
## cont_channel_limited Rating_SE - binary_channel Rating_CC 0.17762
## cont_channel_limited Rating_SE - binary_raidal Rating_CC 0.11500
## cont_channel_limited Rating_SE - cont_channel_limited Rating_CC 0.65500
## cont_channel_limited Rating_SE - cont_channel_ulimited Rating_CC 0.30500
## cont_channel_limited Rating_SE - cont_radial_limited Rating_CC 0.48714
## cont_channel_limited Rating_SE - cont_radial_unlimited Rating_CC 0.26500
## cont_channel_ulimited Rating_SE - cont_radial_limited Rating_SE 0.11048
## cont_channel_ulimited Rating_SE - cont_radial_unlimited Rating_SE 0.09500
## cont_channel_ulimited Rating_SE - binary_channel Rating_CC 0.06762
## cont_channel_ulimited Rating_SE - binary_raidal Rating_CC 0.00500
## cont_channel_ulimited Rating_SE - cont_channel_limited Rating_CC 0.54500
## cont_channel_ulimited Rating_SE - cont_channel_ulimited Rating_CC 0.19500
## cont_channel_ulimited Rating_SE - cont_radial_limited Rating_CC 0.37714
## cont_channel_ulimited Rating_SE - cont_radial_unlimited Rating_CC 0.15500
## cont_radial_limited Rating_SE - cont_radial_unlimited Rating_SE -0.01548
## cont_radial_limited Rating_SE - binary_channel Rating_CC -0.04286
## cont_radial_limited Rating_SE - binary_raidal Rating_CC -0.10548
## cont_radial_limited Rating_SE - cont_channel_limited Rating_CC 0.43452
## cont_radial_limited Rating_SE - cont_channel_ulimited Rating_CC 0.08452
## cont_radial_limited Rating_SE - cont_radial_limited Rating_CC 0.26667
## cont_radial_limited Rating_SE - cont_radial_unlimited Rating_CC 0.04452
## cont_radial_unlimited Rating_SE - binary_channel Rating_CC -0.02738
## cont_radial_unlimited Rating_SE - binary_raidal Rating_CC -0.09000
## cont_radial_unlimited Rating_SE - cont_channel_limited Rating_CC 0.45000
## cont_radial_unlimited Rating_SE - cont_channel_ulimited Rating_CC 0.10000
## cont_radial_unlimited Rating_SE - cont_radial_limited Rating_CC 0.28214
## cont_radial_unlimited Rating_SE - cont_radial_unlimited Rating_CC 0.06000
## binary_channel Rating_CC - binary_raidal Rating_CC -0.06262
## binary_channel Rating_CC - cont_channel_limited Rating_CC 0.47738
## binary_channel Rating_CC - cont_channel_ulimited Rating_CC 0.12738
## binary_channel Rating_CC - cont_radial_limited Rating_CC 0.30952
## binary_channel Rating_CC - cont_radial_unlimited Rating_CC 0.08738
## binary_raidal Rating_CC - cont_channel_limited Rating_CC 0.54000
## binary_raidal Rating_CC - cont_channel_ulimited Rating_CC 0.19000
## binary_raidal Rating_CC - cont_radial_limited Rating_CC 0.37214
## binary_raidal Rating_CC - cont_radial_unlimited Rating_CC 0.15000
## cont_channel_limited Rating_CC - cont_channel_ulimited Rating_CC -0.35000
## cont_channel_limited Rating_CC - cont_radial_limited Rating_CC -0.16786
## cont_channel_limited Rating_CC - cont_radial_unlimited Rating_CC -0.39000
## cont_channel_ulimited Rating_CC - cont_radial_limited Rating_CC 0.18214
## cont_channel_ulimited Rating_CC - cont_radial_unlimited Rating_CC -0.04000
## cont_radial_limited Rating_CC - cont_radial_unlimited Rating_CC -0.22214
## SE df t.ratio p.value
## 0.0729 223 0.621 1.0000
## 0.0729 223 -1.849 0.7886
## 0.0729 223 -0.340 1.0000
## 0.0720 223 1.191 0.9892
## 0.0729 223 0.964 0.9983
## 0.0642 116 0.668 0.9999
## 0.0729 223 -0.271 1.0000
## 0.0729 223 7.139 <.0001
## 0.0729 223 2.336 0.4542
## 0.0720 223 4.896 0.0001
## 0.0729 223 1.787 0.8233
## 0.0738 223 -2.441 0.3835
## 0.0738 223 -0.949 0.9985
## 0.0729 223 0.555 1.0000
## 0.0738 223 0.339 1.0000
## 0.0729 223 -0.033 1.0000
## 0.0658 116 -0.989 0.9977
## 0.0738 223 6.441 <.0001
## 0.0738 223 1.695 0.8689
## 0.0729 223 4.215 0.0021
## 0.0738 223 1.153 0.9918
## 0.0738 223 1.492 0.9416
## 0.0729 223 3.026 0.1081
## 0.0738 223 2.780 0.1961
## 0.0729 223 2.438 0.3855
## 0.0738 223 1.559 0.9216
## 0.0658 116 9.961 <.0001
## 0.0738 223 4.136 0.0029
## 0.0729 223 6.685 <.0001
## 0.0738 223 3.593 0.0202
## 0.0729 223 1.516 0.9348
## 0.0738 223 1.288 0.9799
## 0.0729 223 0.928 0.9988
## 0.0738 223 0.068 1.0000
## 0.0738 223 7.390 <.0001
## 0.0658 116 2.966 0.1326
## 0.0729 223 5.176 <.0001
## 0.0738 223 2.102 0.6221
## 0.0729 223 -0.212 1.0000
## 0.0720 223 -0.595 1.0000
## 0.0729 223 -1.448 0.9525
## 0.0729 223 5.963 <.0001
## 0.0729 223 1.160 0.9913
## 0.0642 116 4.156 0.0035
## 0.0729 223 0.611 1.0000
## 0.0729 223 -0.376 1.0000
## 0.0738 223 -1.220 0.9869
## 0.0738 223 6.102 <.0001
## 0.0738 223 1.356 0.9704
## 0.0729 223 3.872 0.0077
## 0.0658 116 0.912 0.9989
## 0.0729 223 -0.859 0.9994
## 0.0729 223 6.551 <.0001
## 0.0729 223 1.748 0.8436
## 0.0720 223 4.301 0.0015
## 0.0729 223 1.199 0.9886
## 0.0738 223 7.322 <.0001
## 0.0738 223 2.576 0.2997
## 0.0729 223 5.107 <.0001
## 0.0738 223 2.034 0.6698
## 0.0738 223 -4.746 0.0002
## 0.0729 223 -2.304 0.4772
## 0.0738 223 -5.288 <.0001
## 0.0729 223 2.500 0.3457
## 0.0738 223 -0.542 1.0000
## 0.0729 223 -3.049 0.1018
##
## Degrees-of-freedom method: kenward-roger
## P value adjustment: tukey method for comparing a family of 12 estimatest <- confint(t, level = 0.95)
t## contrast estimate
## binary_channel Rating_SE - binary_raidal Rating_SE 0.04524
## binary_channel Rating_SE - cont_channel_limited Rating_SE -0.13476
## binary_channel Rating_SE - cont_channel_ulimited Rating_SE -0.02476
## binary_channel Rating_SE - cont_radial_limited Rating_SE 0.08571
## binary_channel Rating_SE - cont_radial_unlimited Rating_SE 0.07024
## binary_channel Rating_SE - binary_channel Rating_CC 0.04286
## binary_channel Rating_SE - binary_raidal Rating_CC -0.01976
## binary_channel Rating_SE - cont_channel_limited Rating_CC 0.52024
## binary_channel Rating_SE - cont_channel_ulimited Rating_CC 0.17024
## binary_channel Rating_SE - cont_radial_limited Rating_CC 0.35238
## binary_channel Rating_SE - cont_radial_unlimited Rating_CC 0.13024
## binary_raidal Rating_SE - cont_channel_limited Rating_SE -0.18000
## binary_raidal Rating_SE - cont_channel_ulimited Rating_SE -0.07000
## binary_raidal Rating_SE - cont_radial_limited Rating_SE 0.04048
## binary_raidal Rating_SE - cont_radial_unlimited Rating_SE 0.02500
## binary_raidal Rating_SE - binary_channel Rating_CC -0.00238
## binary_raidal Rating_SE - binary_raidal Rating_CC -0.06500
## binary_raidal Rating_SE - cont_channel_limited Rating_CC 0.47500
## binary_raidal Rating_SE - cont_channel_ulimited Rating_CC 0.12500
## binary_raidal Rating_SE - cont_radial_limited Rating_CC 0.30714
## binary_raidal Rating_SE - cont_radial_unlimited Rating_CC 0.08500
## cont_channel_limited Rating_SE - cont_channel_ulimited Rating_SE 0.11000
## cont_channel_limited Rating_SE - cont_radial_limited Rating_SE 0.22048
## cont_channel_limited Rating_SE - cont_radial_unlimited Rating_SE 0.20500
## cont_channel_limited Rating_SE - binary_channel Rating_CC 0.17762
## cont_channel_limited Rating_SE - binary_raidal Rating_CC 0.11500
## cont_channel_limited Rating_SE - cont_channel_limited Rating_CC 0.65500
## cont_channel_limited Rating_SE - cont_channel_ulimited Rating_CC 0.30500
## cont_channel_limited Rating_SE - cont_radial_limited Rating_CC 0.48714
## cont_channel_limited Rating_SE - cont_radial_unlimited Rating_CC 0.26500
## cont_channel_ulimited Rating_SE - cont_radial_limited Rating_SE 0.11048
## cont_channel_ulimited Rating_SE - cont_radial_unlimited Rating_SE 0.09500
## cont_channel_ulimited Rating_SE - binary_channel Rating_CC 0.06762
## cont_channel_ulimited Rating_SE - binary_raidal Rating_CC 0.00500
## cont_channel_ulimited Rating_SE - cont_channel_limited Rating_CC 0.54500
## cont_channel_ulimited Rating_SE - cont_channel_ulimited Rating_CC 0.19500
## cont_channel_ulimited Rating_SE - cont_radial_limited Rating_CC 0.37714
## cont_channel_ulimited Rating_SE - cont_radial_unlimited Rating_CC 0.15500
## cont_radial_limited Rating_SE - cont_radial_unlimited Rating_SE -0.01548
## cont_radial_limited Rating_SE - binary_channel Rating_CC -0.04286
## cont_radial_limited Rating_SE - binary_raidal Rating_CC -0.10548
## cont_radial_limited Rating_SE - cont_channel_limited Rating_CC 0.43452
## cont_radial_limited Rating_SE - cont_channel_ulimited Rating_CC 0.08452
## cont_radial_limited Rating_SE - cont_radial_limited Rating_CC 0.26667
## cont_radial_limited Rating_SE - cont_radial_unlimited Rating_CC 0.04452
## cont_radial_unlimited Rating_SE - binary_channel Rating_CC -0.02738
## cont_radial_unlimited Rating_SE - binary_raidal Rating_CC -0.09000
## cont_radial_unlimited Rating_SE - cont_channel_limited Rating_CC 0.45000
## cont_radial_unlimited Rating_SE - cont_channel_ulimited Rating_CC 0.10000
## cont_radial_unlimited Rating_SE - cont_radial_limited Rating_CC 0.28214
## cont_radial_unlimited Rating_SE - cont_radial_unlimited Rating_CC 0.06000
## binary_channel Rating_CC - binary_raidal Rating_CC -0.06262
## binary_channel Rating_CC - cont_channel_limited Rating_CC 0.47738
## binary_channel Rating_CC - cont_channel_ulimited Rating_CC 0.12738
## binary_channel Rating_CC - cont_radial_limited Rating_CC 0.30952
## binary_channel Rating_CC - cont_radial_unlimited Rating_CC 0.08738
## binary_raidal Rating_CC - cont_channel_limited Rating_CC 0.54000
## binary_raidal Rating_CC - cont_channel_ulimited Rating_CC 0.19000
## binary_raidal Rating_CC - cont_radial_limited Rating_CC 0.37214
## binary_raidal Rating_CC - cont_radial_unlimited Rating_CC 0.15000
## cont_channel_limited Rating_CC - cont_channel_ulimited Rating_CC -0.35000
## cont_channel_limited Rating_CC - cont_radial_limited Rating_CC -0.16786
## cont_channel_limited Rating_CC - cont_radial_unlimited Rating_CC -0.39000
## cont_channel_ulimited Rating_CC - cont_radial_limited Rating_CC 0.18214
## cont_channel_ulimited Rating_CC - cont_radial_unlimited Rating_CC -0.04000
## cont_radial_limited Rating_CC - cont_radial_unlimited Rating_CC -0.22214
## SE df lower.CL upper.CL
## 0.0729 223 -0.1955 0.2859
## 0.0729 223 -0.3755 0.1059
## 0.0729 223 -0.2655 0.2159
## 0.0720 223 -0.1520 0.3235
## 0.0729 223 -0.1705 0.3109
## 0.0642 116 -0.1712 0.2569
## 0.0729 223 -0.2605 0.2209
## 0.0729 223 0.2795 0.7609
## 0.0729 223 -0.0705 0.4109
## 0.0720 223 0.1146 0.5901
## 0.0729 223 -0.1105 0.3709
## 0.0738 223 -0.4236 0.0636
## 0.0738 223 -0.3136 0.1736
## 0.0729 223 -0.2002 0.2812
## 0.0738 223 -0.2186 0.2686
## 0.0729 223 -0.2431 0.2383
## 0.0658 116 -0.2843 0.1543
## 0.0738 223 0.2314 0.7186
## 0.0738 223 -0.1186 0.3686
## 0.0729 223 0.0664 0.5478
## 0.0738 223 -0.1586 0.3286
## 0.0738 223 -0.1336 0.3536
## 0.0729 223 -0.0202 0.4612
## 0.0738 223 -0.0386 0.4486
## 0.0729 223 -0.0631 0.4183
## 0.0738 223 -0.1286 0.3586
## 0.0658 116 0.4357 0.8743
## 0.0738 223 0.0614 0.5486
## 0.0729 223 0.2464 0.7278
## 0.0738 223 0.0214 0.5086
## 0.0729 223 -0.1302 0.3512
## 0.0738 223 -0.1486 0.3386
## 0.0729 223 -0.1731 0.3083
## 0.0738 223 -0.2386 0.2486
## 0.0738 223 0.3014 0.7886
## 0.0658 116 -0.0243 0.4143
## 0.0729 223 0.1364 0.6178
## 0.0738 223 -0.0886 0.3986
## 0.0729 223 -0.2562 0.2252
## 0.0720 223 -0.2806 0.1949
## 0.0729 223 -0.3462 0.1352
## 0.0729 223 0.1938 0.6752
## 0.0729 223 -0.1562 0.3252
## 0.0642 116 0.0526 0.4807
## 0.0729 223 -0.1962 0.2852
## 0.0729 223 -0.2681 0.2133
## 0.0738 223 -0.3336 0.1536
## 0.0738 223 0.2064 0.6936
## 0.0738 223 -0.1436 0.3436
## 0.0729 223 0.0414 0.5228
## 0.0658 116 -0.1593 0.2793
## 0.0729 223 -0.3033 0.1781
## 0.0729 223 0.2367 0.7181
## 0.0729 223 -0.1133 0.3681
## 0.0720 223 0.0718 0.5473
## 0.0729 223 -0.1533 0.3281
## 0.0738 223 0.2964 0.7836
## 0.0738 223 -0.0536 0.4336
## 0.0729 223 0.1314 0.6128
## 0.0738 223 -0.0936 0.3936
## 0.0738 223 -0.5936 -0.1064
## 0.0729 223 -0.4086 0.0728
## 0.0738 223 -0.6336 -0.1464
## 0.0729 223 -0.0586 0.4228
## 0.0738 223 -0.2836 0.2036
## 0.0729 223 -0.4628 0.0186
##
## Degrees-of-freedom method: kenward-roger
## Confidence level used: 0.95
## Conf-level adjustment: tukey method for comparing a family of 12 estimatest <- subset(t, contrast == "binary_channel Rating_SE - binary_channel Rating_CC" |
contrast == "binary_raidal Rating_SE - binary_raidal Rating_CC" |
contrast == "cont_channel_limited Rating_SE - cont_channel_limited Rating_CC" |
contrast == "cont_radial_limited Rating_SE - cont_radial_limited Rating_CC" |
contrast == "cont_channel_ulimited Rating_SE - cont_channel_ulimited Rating_CC" |
contrast == "cont_radial_unlimited Rating_SE - cont_radial_unlimited Rating_CC")
# binary channel
lo <- t[1,5]
hi <- t[1,6]
(bin_channel_width <- hi - lo)## [1] 0.428117(bin_channel_width_moe <- (hi - lo)/2)## [1] 0.2140585# binary radial
lo <- t[2,5]
hi <- t[2,6]
(bin_radial_width <- hi - lo)## [1] 0.4386894(bin_radial_width_moe <- (hi - lo)/2)## [1] 0.2193447# cont channel limited
lo <- t[3,5]
hi <- t[3,6]
(cont_channel_limited_width <- hi - lo)## [1] 0.4386894(cont_channel_limited_width_moe <- (hi - lo)/2)## [1] 0.2193447# cont radial limited
lo <- t[4,5]
hi <- t[4,6]
(cont_radial_limited_width <- hi - lo)## [1] 0.4386894(cont_radial_limited_width_moe <- (hi - lo)/2)## [1] 0.2193447# cont channel unlimited
lo <- t[5,5]
hi <- t[5,6]
(cont_channel_unlimited_width <- hi - lo)## [1] 0.428117(cont_channel_unlimited_width_moe <- (hi - lo)/2)## [1] 0.2140585# cont radial unlimited
lo <- t[6,5]
hi <- t[6,6]
(cont_radial_unlimited_width <- hi - lo)## [1] 0.4386894(cont_radial_unlimited_width_moe <- (hi - lo)/2)## [1] 0.2193447cond <- c("bin_channel_width", "bin_radial_width", "cont_channel_limited_width", "cont_radial_limited_width",
"cont_channel_unlimited_width", "cont_radial_unlimited_width")
ci_width <- c(bin_channel_width, bin_radial_width, cont_channel_limited_width, cont_radial_limited_width,
cont_channel_unlimited_width, cont_radial_unlimited_width)
CI_widths <- data.frame(cond, ci_width)t$contrast <- factor(t$contrast, levels = c("binary_raidal Rating_SE - binary_raidal Rating_CC",
"binary_channel Rating_SE - binary_channel Rating_CC",
"cont_radial_unlimited Rating_SE - cont_radial_unlimited Rating_CC",
"cont_channel_ulimited Rating_SE - cont_channel_ulimited Rating_CC",
"cont_radial_limited Rating_SE - cont_radial_limited Rating_CC",
"cont_channel_limited Rating_SE - cont_channel_limited Rating_CC"),
labels = c("binary-radial",
"binary-channel",
"cont.-radial-unlimited",
"cont.-channel-unlimited",
"cont.-radial-limited",
"cont.-channel-limited"
)
)7 Additional summary graph
## Warning: Ignoring unknown aesthetics: y